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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Dan Guo Hui Wang Hanwang Zhang Zheng-Jun Zha Meng Wang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Nanyang Technological University University of Science and Technology of China

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

Visual dialog is a challenging task that requires the comprehension of the semantic dependencies among implicit visual and textual contexts. This task can refer to the relation inference in a graphical model with sparse contexts and unknown graph structure (relation descriptor), and how to model the underlying context-aware relation inference is critical. To this end, we propose a novel Context-Aware Graph (CAG) neural network. Each node in the graph corresponds to a joint semantic feature, including both object-based (visual) and history-related (textual) context representations. The graph structure (relations in dialog) is iteratively updated using an adaptive top-K message passing mechanism. Specifically, in every message passing step, each node selects the most K relevant nodes, and only receives messages from them. Then, after the update, we impose graph attention on all the nodes to get the final graph embedding and infer the answer. In CAG, each node has dynamic relations in the graph (different related K neighbor nodes), and only the most relevant nodes are attributive to the context-aware relational graph inference. Experimental results on VisDial v0.9 and v1.0 datasets show that CAG outperforms comparative methods. Visualization results further validate the interpretability of our method.

关键词： Visualization History Task analysis Semantics Message passing Neural networks Cognition

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Application and development of elastic fibers focusing on composition and structure 6

Application and development of elastic fibers focusing on co...

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2021 6th International Seminar on Advances in Materials Science and engineering, ISAMSE 2021

作者： Zhang, Jin Sun, Qinyue Wang, Yumin Dong, Xiongwei Xiong, Yi Zeng, Wei Department of Pharmacy Zhongnan Hospital Wuhan University Wuhan430071 China Science and Technology Institute Key Laboratory of Textile Fiber and Products Ministry of Education Laboratory for Electron Microscopy Wuhan Textile University Hubei Wuhan430073 China National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information Engineering Anhui University Anhui Hefei230601 China School of Physics and Technology MOE Key Laboratory of Artificial Micro- and Nano-Structures Wuhan University Wuhan430072 China

Elastic fabric is comfortable to wear, and has been a consumer textile due to its good shape retention and wrinkle resistance after washing. This paper briefly introduces the types and performance characteristics of several common elastic fibers, and analyzes the relationship between the structure and elasticity of different elastic fibers. Finally, the development trend of elastic fibers is proposed. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Elasticity

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Combining Global and Sequential Patterns for Multivariate Time Series Forecasting

Combining Global and Sequential Patterns for Multivariate Ti...

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IEEE International Conference on Big data

作者： Zhaoxi Li Jun He Hongyan Liu Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China School of Economics and Management Tsinghua g University Beijing China

ISBN: (数字)9781728162515

ISBN: (纸本)9781728162522

Multivariate time series forecasting is very important for many applications. Many studies have been conducted for accurate and interpretable prediction methods. However, existing methods either cannot take both times series and covariates into consideration, lacking of interpretability, or ignore global trends across multivariate time series. In this paper, we aim to solve these issues. To this end, we propose a new model named TEDGE for accurate and interpretable time series prediction. In this model, we extract global trends hidden across multivariate times series to improve prediction accuracy. Meanwhile, we utilize a deep recurrent model with attention mechanism to find long-and short-term sequential patterns hidden in individual time series with interpretability. We conduct experiments on several datasets to evaluate the proposed models performance. Results demonstrate the superior performance of our proposed model.

关键词： Conferences Time series analysis Predictive models Big data Market research data models Forecasting

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QUANTUM LOVÁSZ LOCAL LEMMA: SHEARER’S BOUND IS TIGHT

arXiv

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arXiv 2018年

作者： He, Kun Li, Qian Sun, Xiaoming Zhang, Jiapeng The Key Lab of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China University of Southern California United States

The Lovász Local Lemma (LLL) is a very powerful tool in combinatorics and probability theory to show the possibility of avoiding all bad events under some weakly dependent conditions. In a seminal paper, Ambainis, Kempe, and Sattath (JACM 2012) introduced a quantum version LLL (QLLL) which shows the possibility of avoiding all "bad" Hamiltonians under some weakly dependent condition, and applied QLLL to the random k-QSAT problem. Sattath, Morampudi, Laumann, and moessner (PNAS 2015) extended Ambainis, Kempe, and Sattath’s result and showed that Shearer’s bound is a sufficient condition for QLLL, and conjectured that Shearer’s bound is indeed the tight condition for QLLL. In this paper, we affirm this conjecture. Precisely, we prove that Shearer’s bound is tight for QLLL, i.e., the relative dimension of the smallest satisfying subspace is completely characterized by the independent set polynomial. Our result implies the tightness of Gilyén and Sattath’s algorithm (FOCS 2017), and also implies that the lattice gas partition function fully characterizes quantum satisfiability for almost all Hamiltonians with large enough qudits (Sattath, Morampudi, Laumann and moessner, PNAS 2015). The commuting LLL (CLLL), which focuses on commuting local Hamiltonians, is also investigated here. We prove that the tight regions of CLLL and QLLL are different in general. This result indicates that it is possible to design an algorithm for CLLL which is still efficient beyond Shearer’s bound. Copyright © 2018, The Authors. All rights reserved.

关键词： Hamiltonians

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A Secure Collusion-Aware and Probability-Aware Range Query Processing in Tiered Sensor Networks

A Secure Collusion-Aware and Probability-Aware Range Query P...

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Reliable Distributed Systems

作者： Lei Dong Xuan Chen Jianxiang Zhu Hong Chen Ke Wang Cuiping Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Beijing China School of Information Renmin University of China Beijing China School of Computing Science Simon Fraser University Burnaby BC Canada Key Lab. of Data Eng. & Knowledge Eng. of Minist. of Educ. Beijing China

With high expansibility and efficient power usage, tiered wireless sensor networks are widely deployed in many fields as an important part of Internet of Things (IoTs). It is challenging to process range query while protecting sensitive data from adversaries. Moreover, most existing work focuses on privacy-preserving range query neglecting collusion attacks and probability attacks, which are more threatening to network security. In this paper, we first propose a secure range query protocol called secRQ, which not only protects data privacy, but also resists collusion attacks and probability attacks in tiered wireless sensor networks. Generalized inverse matrices and distance-based range query mechanism are used to guarantee security as well as high efficiency and accuracy. Besides, we propose the mutual verification scheme to verify the integrity of query results. Finally, both theoretical analysis and experimental results confirm the security, efficiency and accuracy of secRQ.

关键词： Wireless sensor networks Protocols data privacy Biomedical monitoring Query processing Monitoring Heart rate

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A Coffee-Ring Effect-Based Paper Sensor Chip for the Determination of Β-Lactoglobulin in Foods Via a Smartphone

SSRN

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SSRN 2022年

作者： Lu, Yang Yang, Jingyi Zhang, Yong Wu, Lin State Key Laboratory for Food Nutrition and Safety College of Food Science and Engineering Tianjin University of Science and Technology Tianjin300457 China State Key Laboratory of Knowledge Engineering with Big Data School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China

To determine allergen β-lactoglobulin (β-LG) in foods, a method by a coffee-ring effect (CRE)-based paper sensor chip combined with a smartphone has been developed. The strategy was based on the principle of fluorescence quenching by the quantum dot-aptamer-graphene oxide (QD-Apt-GO) and where the degree of quenching was inversely proportional to the concentration of β-LG. First, the prepared β-LG solution was added to the QD-aptamer fluorescent probe solution followed by an appropriate amount of GO. After the reaction, a certain amount of the mixture was dispensed onto the detection zone of the sensor chip, resulting in the spread of the analyte solution by evaporation-driven flow. The QD-aptamer and the QD-Apt-β-LG in the mixed solution formed a visible fluorescent coffee-ring. For signal quantitation, an image of the coffee-ring was taken by a smartphone and imported into self-programmed software for analysis. The quantitative results for β-LG were acquired rapidly based on the magnitude of the generated fluorescent coffee-ring. The limit of detection (LOD) for β-LG was 0.048 mg L -1 and the linear range for the optimized assay was 0.39–1000 mg L -1 . The method was validated for analysis of real food samples and the results were consistent with those of a commercial ELISA assay kit. The smartphone-based assay provides a simple, economic, compact, and visual detection platform for the determination of β-LG in foods. © 2022, The Authors. All rights reserved.

关键词： Graphene

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Photothermal and pH dual-responsive self-healing coating for smart corrosion protection

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Journal of Materials Science & Technology 2022年第12期107卷 34-42页

作者： Yao Huang Panjun Wang Weimin Tan Wenkui Hao Lingwei Ma Jinke Wang Tong Liu Fan Zhang Chenhao Ren Wei Liu Dawei Zhang Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China National Engineering Research Center for Coatings CNOOC Changzhou Paint and Coatings Industry Research InstituteChangzhou 213016China State Key Laboratory of Advanced Power Transmission Technology(Global Energy Interconnection Research Institute Co.Ltd. )Beijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528300China

A novel self-healing coating with photothermal and pH dual-responsive properties has been designed to protect carbon steel against corrosion by loading the stimuli-responsive microcapsules into a shape memory epoxy coating. The sandwich-like microcapsules were based on reduced graphene oxide/mesoporous silica(r GO@MS) assembled with a p H-responsive poly(N,N-dimethylaminoethyl methacrylate)(PDMAEMA) layer, and were loaded with benzotriazole(BTA) inhibitors(abbreviated as rGO@MS-P-BTA). Under near-infrared(NIR) light irradiation, the prominent photothermal effect of rGO could not only elevate the coating temperature to activate the shape memory effect and close the coating scratch, but also facilitate the release of corrosion inhibitors to suppress the corrosion activity. Moreover,the PDMAEMA as a p H-driven “gatekeeper” realized the controlled release of BTA from microcapsules at acid conditions. The surface morphology analysis, electrochemical impedance spectroscopy(EIS), and scanning electrochemical microscopy(SECM) were performed to evaluate the self-healing performance of the composite coatings. The results showed that the combination of NIR light and p H-responsive selfhealing effects endowed the coating with short healing time and prominent healing efficiency.

关键词： Self-healing coatings Corrosion inhibitors Photothermal effects pH-responsive Shape memory polymers

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Improving the microenvironment of tracking photovoltaic systems promotes soil organic carbon accumulation by mediating plant carbon inputs and microbial necromass retention

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Journal of Environmental Management 2025年 388卷 125937页

作者： Siqi Zhang Jirui Gong Rui Wang Kai Zheng Weiyuan Zhang Xuede Dong Yuxia Hu Guisen Yang Chenyi Yan Shangpeng Zhang Ruijing Wang Tong Wang State Key Laboratory of Earth Surface Processes and Resource Ecology MOE Engineering Research Center of Desertification and Blown-sand Control Faculty of Geographical Science Beijing Normal University No. 19 Xinjiekouwai Street Haidian District Beijing 100875 China CGN New Energy Holdings Co. Ltd. Hanwei International Plaza Fengtai District Beijing 100071 China Inner Mongolia Ganze Desert Technology Co. Ltd. High-tech industrial park cloud computing big data enterprise headquarters Kangbashi District Ordos 017004 China

Photovoltaic systems greatly reduce greenhouse gas emissions. However, the microenvironmental changes of photovoltaic modules affect soil organic carbon (SOC) and improve carbon sequestration in terrestrial ecosystems to mitigate global climate change is unclear. We analyzed the effects of different photovoltaic systems on SOC and its fractions in semi-arid grassland, and revealed the SOC formation and stability mechanisms. Tracking photovoltaic systems increased carbon stock, especially proportion of mineral-associated organic carbon (MAOC) in SOC by more than 10 %, and depended on the responses of plant inputs and microbial necromass to microenvironmental changes. Suitable amounts of light and water in the systems improved litter biomass and quality, and promoted MAOC accumulation by increasing the exogenous carbon supply and microbial activity. Such systems also reduced soil carbon loss by reducing heterotrophic respiration caused by low levels of organic acids and recruiting effective microorganisms such as Schizothecium and Lactobacillus . Moreover, changes in litter and root exudates promoted microbial biomass and enzyme activity, mediating the retention of microbial necromass and SOC. The contribution of bacterial necromass carbon to SOC increased by more than 8.5 %. However, fixed photovoltaic systems reduced soil carbon stock by 0.46 kg m −2 due to water limitations that decreased both plant carbon inputs and microbial necromass. Our results revealed the importance of plant inputs and microbial necromass in regulating SOC in photovoltaic systems, and demonstrated that photovoltaic systems can achieve synergies between CO 2 emission reduction and soil carbon sequestration. This provides new insights for formulating carbon management policy and promoting sustainable eco-economic development.

关键词： Litter quantity and quality Microbial necromass Photovoltaic system Root exudates Soil microbes Soil organic carbon

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Τ-FPL: Tolerance-constrained learning in linear time 32

Τ-FPL: Tolerance-constrained learning in linear time

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32nd AAAI Conference on Artificial Intelligence, AAAI 2018

作者： Zhang, Ao Li, Nan Pu, Jian Wang, Jun Yan, Junchi Zha, Hongyuan Shanghai Key Laboratory of Trustworthy Computing MOE International Joint Lab of Trustworthy Software School of Computer Science and Software Engineering East China Normal University Shanghai China Institute of Data Science and Technologies Alibaba Group Hangzhou China IBM Research China Georgia Institute of Technology Atlante United States

ISBN: (纸本)9781577358008

In many real-world applications, learning a classifier with false-positive rate under a specified tolerance is appealing. Existing approaches either introduce prior knowledge dependent label cost or tune parameters based on traditional classifiers, which are of limitation in methodology since they do not directly incorporate the false-positive rate tolerance. In this paper, we propose a novel scoring-thresholding approach, τ-False Positive Learning (τ-FPL) to address this problem. We show that the scoring problem which takes the false-positive rate tolerance into accounts can be efficiently solved in linear time, also an out-of-bootstrap thresholding method can transform the learned ranking function into a low false-positive classifier. Both theoretical analysis and experimental results show superior performance of the proposed τ-FPL over the existing approaches. Copyright © 2018, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Mathematical transformations

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A Query-Oriented Summarization System for XML Elements

A Query-Oriented Summarization System for XML Elements

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International Conference on Management of e-Commerce and e-Government, ICMECG

作者： Dexi Liu Shihan Wu Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China Songjiang Branch of Shanghai Rural Commercial Bank Shanghai China

In document-center XML dataset, an element may contain so many text that users have to spend enough time to judge the elements returned by XML search engine are valuable or not. Query-orient XML summarization system aim to provide users a brief and readable substitution of the original retrieved elements according to the user's query, which can relieve user's reading burden effectively. In this work, we extract sentences from the results of XML search engine, and combine them as a summary. Experiments on the IEEE-CS datasets used in INEX show that, the query-oriented XML summary generated by our method is reasonable.

关键词： XML Feature extraction Sections Search engines Computational modeling Electronic mail

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